首页|Investigators at Xiamen University Describe Findings in Machine Translation (A M ultitask Co-training Framework for Improving Speech Translation By Leveraging Sp eech Recognition and Machine Translation Tasks)
Investigators at Xiamen University Describe Findings in Machine Translation (A M ultitask Co-training Framework for Improving Speech Translation By Leveraging Sp eech Recognition and Machine Translation Tasks)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Translation h ave been presented. According to newsoriginating from Xiamen, People’s Republic of China, by NewsRx correspondents, research stated, “Endto-end speech transla tion (ST) has attracted substantial attention due to its less error accumulation andlower latency. Based on triplet ST data \document class[12pt]{minimal} \ usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \ usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \ usepackage{upgreek} \setlength{ \oddsidemargin}{-69pt} \ begin{document}$$\ langle$$\end{do cument} speech-transcription-translation \documentcl ass[12pt]{minimal} \ usepackage{amsmath}\usepackage{ wasysym} \usepackage{amsfonts} \ usepackage{amssymb} \usepackage{ amsbsy}\usepackage{mathrsfs} \ usepackage{upgreek} \setlength{ \oddsidemargin}{-69pt} \ begin{document}$$\ rangle$$\end{do cument}, multitask learning (MTL) that utilizes machine translation \documentclass[12pt] {minimal} \usepackage{amsm ath} \usepackage{wasysym} \ usepackage{amsfonts} \usepackage{ amssymb} \usepackage{amsbsy} \ usepackage{mathrsfs} \usepackage{ upgreek} \setlength{\ oddsidemargin}{-69pt} \beg in{document}$$\ langle$$\end{do cument}transcription-translation \documentclass[12pt]{minimal} \ usepackage{amsmath} \usepackage{ wasysym} \usepackage{amsfonts} \ usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \ usepackage{upgreek} \setlength{ oddsidemargin}{-69pt} \ begin{document}$$\ rangle$$\end{do cument} or automatic speech recognition\documentcla ss[12pt]{minimal} \ usepackage{amsmath} \usepackage{ wasysym} \usepackage{amsfonts}\ usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \ usepackage{upgreek} setlength{ \oddsidemargin}{-69pt} \ begin{document}$$\ langle$$\end{do cument}speech-transcription\documentclas s[12pt]{minimal} \ usepackage{amsmath} \usepackage{ wasysym} \usepackage{amsfonts}\ usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \ usepackage{upgreek} \setlength{ \oddsidemargin}{-69pt} \ begin{document}$$\ rangle$$\end{do cument} task to assist intraining ST model is widely employed.”
XiamenPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningMachine TranslationXiamen Universit y
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